Scaling up the Naive Bayesian Classifier : Using Decision Trees for Feature Selection

@inproceedings{Ratanamahatana2002ScalingUT,
  title={Scaling up the Naive Bayesian Classifier : Using Decision Trees for Feature Selection},
  author={Chotirat Ratanamahatana and Dimitrios Gunopulos},
  year={2002}
}
It is known that Naïve Bayesian classifier (NB) works very well on some domains, and poorly on some. The performance of NB suffers in domains that involve correlated features. C4.5 decision trees, on the other hand, typically perform better than the Naïve Bayesian algorithm on such domains. This paper describes a Selective Bayesian classifier (SBC) that simply uses only those features that C4.5 would use in its decision tree when learning a small example of a training set, a combination of the… CONTINUE READING
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